Birth weight and illness severity: independent predictors of neonatal mortality.

BACKGROUND: Low birth weight is a major determinant of neonatal mortality. Yet birth weight, even in conjunction with other demographic markers, is inadequate to explain the large variations in neonatal mortality between intensive care units. This variation probably reflects differences in admission severity. The authors have recently developed the Score for Neonatal Acute Physiology (SNAP), an illness severity index specific for neonatal intensive care, and demonstrated illness severity to be a major determinant of neonatal mortality.
OBJECTIVE: To define the relative contributions of birth weight and illness severity to the risk of neonatal mortality and to identify other significant independent risk factors.
METHODS: Logistic regression was used to analyze data from a cohort of 1621 consecutive admissions to three neonatal intensive care units (92 deaths), to test six alternative predictive models. The best logistic model was then used to develop a simple additive clinical score, the SNAP Perinatal Extension (SNAP-PE).
RESULTS: These analyses demonstrated that birth weight and illness severity are powerful independent predictors across a broad range of birth weights and that their effects are additive. Below 750 g, there is an interaction between birth weight and SNAP. Other factors that showed independent predictive power were low Apgar score at 5 minutes and small size for gestational age. Separate derivation and test samples were used to demonstrate that the SNAP-PE is comparable to the best logistic model and has a sensitivity and specificity superior to either birth weight or SNAP alone (receiver-operator characteristic area .92 +/- .02) as well as excellent goodness of fit.
CONCLUSION: This simplified clinical score provides accurate mortality risk estimates for application in a broad array of clinical and research settings.